The role of <i>rpoS</i> on the survival of a <i>p</i>-nitrophenol degrading <i>Pseudomonas putida</i> strain in planktonic and biofilm phases
Bibliographic record
Abstract
The survival of and interactions between a Pseudomonas putida strain labelled with a red fluorescent protein gene (WT-rfp) and its green fluorescent protein gene-labelled rpoS(-) mutant (KO-gfp) were examined. The generation times of the planktonic WT-rfp and KO-gfp in trypticase soy broth were not significantly different (i.e., p > 0.05) from each other at 30 degrees C. However, the biovolume of the KO-gfp biofilm was about 7 times larger than its WT-rfp counterpart after 48 h of growth. Furthermore, the presence of WT-rfp suppressed the biofilm development of KO-gfp significantly in co-culture biofilms. In planktonic conditions, the pre-carbon-starved WT-rfp achieved a 3-fold greater survival than the pre-carbon-starved KO-gfp in 0.85% saline after a 13-day incubation. In a 1:1 ratio co-culture, the pre-carbon-starved WT-rfp outcompeted the pre-carbon-starved KO-gfp by 20-fold. However, the survival of WT-rfp and KO-gfp were not significantly different from each other in biofilm conditions. Additionally, 11.4% and 61.2% of the WT-rfp and KO-gfp biofilms, respectively, remained intact after washing in 0.2% SDS for 60 min. In conclusion, the rpoS had a significant impact on survival and competitiveness of planktonic P. putida, and on biofilm development, being implicated in competitive suppression of biofilm development in co-culture biofilms and decreased biofilm cohesiveness.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".